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Building Predictive Models in R Using the caret Package

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Cited by:

  1. Anurag Satpathi & Parul Setiya & Bappa Das & Ajeet Singh Nain & Prakash Kumar Jha & Surendra Singh & Shikha Singh, 2023. "Comparative Analysis of Statistical and Machine Learning Techniques for Rice Yield Forecasting for Chhattisgarh, India," Sustainability, MDPI, vol. 15(3), pages 1-18, February.
  2. Adam P. Dixon & Matthew E. Baker & Erle C. Ellis, 2020. "Agricultural Landscape Composition Linked with Acoustic Measures of Avian Diversity," Land, MDPI, vol. 9(5), pages 1-18, May.
  3. László Pásztor & Katalin Takács & János Mészáros & Gábor Szatmári & Mátyás Árvai & Tibor Tóth & Gyöngyi Barna & Sándor Koós & Zsófia Adrienn Kovács & Péter László & Kitti Balog, 2023. "Indirect Prediction of Salt Affected Soil Indicator Properties through Habitat Types of a Natural Saline Grassland Using Unmanned Aerial Vehicle Imagery," Land, MDPI, vol. 12(8), pages 1-23, July.
  4. Shearman, Timothy M. & Varner, J. Morgan & Hood, Sharon M. & Cansler, C. Alina & Hiers, J. Kevin, 2019. "Modelling post-fire tree mortality: Can random forest improve discrimination of imbalanced data?," Ecological Modelling, Elsevier, vol. 414(C).
  5. Johann Baumgartner & Katharina Gruber & Sofia G. Simoes & Yves-Marie Saint-Drenan & Johannes Schmidt, 2020. "Less Information, Similar Performance: Comparing Machine Learning-Based Time Series of Wind Power Generation to Renewables.ninja," Energies, MDPI, vol. 13(9), pages 1-23, May.
  6. Yam Bahadur KC & Qijing Liu & Pradip Saud & Damodar Gaire & Hari Adhikari, 2024. "Estimation of Above-Ground Forest Biomass in Nepal by the Use of Airborne LiDAR, and Forest Inventory Data," Land, MDPI, vol. 13(2), pages 1-18, February.
  7. Arthur Novaes de Amorim & Rob Deardon & Vineet Saini, 2021. "A stacked ensemble method for forecasting influenza-like illness visit volumes at emergency departments," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-15, March.
  8. Abhinav Vepa & Amer Saleem & Kambiz Rakhshan & Alireza Daneshkhah & Tabassom Sedighi & Shamarina Shohaimi & Amr Omar & Nader Salari & Omid Chatrabgoun & Diana Dharmaraj & Junaid Sami & Shital Parekh &, 2021. "Using Machine Learning Algorithms to Develop a Clinical Decision-Making Tool for COVID-19 Inpatients," IJERPH, MDPI, vol. 18(12), pages 1-22, June.
  9. Zhuoran Xu & Quan Li & Luigi Marchionni & Kai Wang, 2023. "PhenoSV: interpretable phenotype-aware model for the prioritization of genes affected by structural variants," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
  10. Merlijn Breugel & Cancan Qi & Zhongli Xu & Casper-Emil T. Pedersen & Ilya Petoukhov & Judith M. Vonk & Ulrike Gehring & Marijn Berg & Marnix Bügel & Orestes A. Carpaij & Erick Forno & Andréanne Morin , 2022. "Nasal DNA methylation at three CpG sites predicts childhood allergic disease," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  11. Miguel Godinho de Matos & Pedro Ferreira & Michael D. Smith, 2018. "The Effect of Subscription Video-on-Demand on Piracy: Evidence from a Household-Level Randomized Experiment," Management Science, INFORMS, vol. 64(12), pages 5610-5630, December.
  12. Mirza Čengić & Zoran J. N. Steinmann & Pierre Defourny & Jonathan C. Doelman & Céline Lamarche & Elke Stehfest & Aafke M. Schipper & Mark A. J. Huijbregts, 2023. "Global Maps of Agricultural Expansion Potential at a 300 m Resolution," Land, MDPI, vol. 12(3), pages 1-13, February.
  13. Xiao Xu & Meera Ramanujam & Sudha Visvanathan & Shervin Assassi & Zheng Liu & Li Li, 2020. "Transcriptional insights into pathogenesis of cutaneous systemic sclerosis using pathway driven meta-analysis assisted by machine learning methods," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-20, November.
  14. Prabal Das & D. A. Sachindra & Kironmala Chanda, 2022. "Machine Learning-Based Rainfall Forecasting with Multiple Non-Linear Feature Selection Algorithms," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 6043-6071, December.
  15. Jie Zhao & Ji Chen & Damien Beillouin & Hans Lambers & Yadong Yang & Pete Smith & Zhaohai Zeng & Jørgen E. Olesen & Huadong Zang, 2022. "Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  16. Miriam Steurer & Robert Hill, 2019. "Metrics for Evaluating the Performance of Automated Valuation Models," Graz Economics Papers 2019-02, University of Graz, Department of Economics.
  17. Antonio Rodríguez Andrés & Abraham Otero & Voxi Heinrich Amavilah, 2022. "Knowledge economy classification in African countries: A model-based clustering approach," Information Technology for Development, Taylor & Francis Journals, vol. 28(2), pages 372-396, April.
  18. Bellotti, Anthony & Brigo, Damiano & Gambetti, Paolo & Vrins, Frédéric, 2021. "Forecasting recovery rates on non-performing loans with machine learning," International Journal of Forecasting, Elsevier, vol. 37(1), pages 428-444.
  19. Piaopiao Chen & Agnès H. Michel & Jianzhi Zhang, 2022. "Transposon insertional mutagenesis of diverse yeast strains suggests coordinated gene essentiality polymorphisms," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  20. Zakia Salod & Ozayr Mahomed, 2023. "VPAgs-Dataset4ML: A Dataset to Predict Viral Protective Antigens for Machine Learning-Based Reverse Vaccinology," Data, MDPI, vol. 8(2), pages 1-12, February.
  21. Distaso, Walter & Roccazzella, Francesco & Vrins, Frédéric, 2023. "Business cycle and realized losses in the consumer credit industry," LIDAM Discussion Papers LFIN 2023007, Université catholique de Louvain, Louvain Finance (LFIN).
  22. Paulo Infante & Gonçalo Jacinto & Anabela Afonso & Leonor Rego & Pedro Nogueira & Marcelo Silva & Vitor Nogueira & José Saias & Paulo Quaresma & Daniel Santos & Patrícia Góis & Paulo Rebelo Manuel, 2023. "Factors That Influence the Type of Road Traffic Accidents: A Case Study in a District of Portugal," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
  23. Yane Freitas Silva & Rafael Vasconcelos Valadares & Henrique Boriolo Dias & Santiago Vianna Cuadra & Eleanor E. Campbell & Rubens A. C. Lamparelli & Edemar Moro & Rafael Battisti & Marcelo R. Alves & , 2022. "Intense Pasture Management in Brazil in an Integrated Crop-Livestock System Simulated by the DayCent Model," Sustainability, MDPI, vol. 14(6), pages 1-24, March.
  24. Amparo Baíllo & Javier Cárcamo & Konstantin Getman, 2019. "New distance measures for classifying X-ray astronomy data into stellar classes," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(2), pages 531-557, June.
  25. Xavier Santamaria & Beatriz Roson & Raul Perez-Moraga & Nandakumar Venkatesan & Maria Pardo-Figuerez & Javier Gonzalez-Fernandez & Jaime Llera-Oyola & Estefania Fernández & Inmaculada Moreno & Andres , 2023. "Decoding the endometrial niche of Asherman’s Syndrome at single-cell resolution," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
  26. Matthew Harding & Gabriel F. R. Vasconcelos, 2022. "Managers versus Machines: Do Algorithms Replicate Human Intuition in Credit Ratings?," Papers 2202.04218, arXiv.org.
  27. Arnaldo Rabello de Aguiar Vallim Filho & Daniel Farina Moraes & Marco Vinicius Bhering de Aguiar Vallim & Leilton Santos da Silva & Leandro Augusto da Silva, 2022. "A Machine Learning Modeling Framework for Predictive Maintenance Based on Equipment Load Cycle: An Application in a Real World Case," Energies, MDPI, vol. 15(10), pages 1-41, May.
  28. Ephrem Habyarimana & Faheem S Baloch, 2021. "Machine learning models based on remote and proximal sensing as potential methods for in-season biomass yields prediction in commercial sorghum fields," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
  29. Khan, Muhammad Asif & Segovia, Juan E.Trinidad & Bhatti, M.Ishaq & Kabir, Asif, 2023. "Corporate vulnerability in the US and China during COVID-19: A machine learning approach," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
  30. Amit Kumar Srivastava & Suranjana Bhaswati Borah & Payel Ghosh Dastidar & Archita Sharma & Debabrat Gogoi & Priyanuz Goswami & Giti Deka & Suryakanta Khandai & Rupam Borgohain & Sudhanshu Singh & Asho, 2023. "Rice-Fallow Targeting for Cropping Intensification through Geospatial Technologies in the Rice Belt of Northeast India," Agriculture, MDPI, vol. 13(8), pages 1, July.
  31. Droste, N. & Ring, I. & Santos, R. & Kettunen, M., 2018. "Ecological Fiscal Transfers in Europe – Evidence-Based Design Options for a Transnational Scheme," Ecological Economics, Elsevier, vol. 147(C), pages 373-382.
  32. Brédy, Jhemson & Gallichand, Jacques & Celicourt, Paul & Gumiere, Silvio José, 2020. "Water table depth forecasting in cranberry fields using two decision-tree-modeling approaches," Agricultural Water Management, Elsevier, vol. 233(C).
  33. Franzin, Alberto & Stützle, Thomas, 2023. "A landscape-based analysis of fixed temperature and simulated annealing," European Journal of Operational Research, Elsevier, vol. 304(2), pages 395-410.
  34. Banks, Jonathan & Rabbani, Arif & Nadkarni, Kabir & Renaud, Evan, 2020. "Estimating parasitic loads related to brine production from a hot sedimentary aquifer geothermal project: A case study from the Clarke Lake gas field, British Columbia," Renewable Energy, Elsevier, vol. 153(C), pages 539-552.
  35. Mielniczuk, Jan & Teisseyre, Paweł, 2014. "Using random subspace method for prediction and variable importance assessment in linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 725-742.
  36. Sek Won Kong & Christin D Collins & Yuko Shimizu-Motohashi & Ingrid A Holm & Malcolm G Campbell & In-Hee Lee & Stephanie J Brewster & Ellen Hanson & Heather K Harris & Kathryn R Lowe & Adrianna Saada , 2012. "Characteristics and Predictive Value of Blood Transcriptome Signature in Males with Autism Spectrum Disorders," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-13, December.
  37. Giovanny Pillajo-Quijia & Blanca Arenas-Ramírez & Camino González-Fernández & Francisco Aparicio-Izquierdo, 2020. "Influential Factors on Injury Severity for Drivers of Light Trucks and Vans with Machine Learning Methods," Sustainability, MDPI, vol. 12(4), pages 1-28, February.
  38. Hossain, Marup & Mullally, Conner & Asadullah, M. Niaz, 2019. "Alternatives to calorie-based indicators of food security: An application of machine learning methods," Food Policy, Elsevier, vol. 84(C), pages 77-91.
  39. Rydberg Roman Supo-Escalante & Aldhair Médico & Eduardo Gushiken & Gustavo E Olivos-Ramírez & Yaneth Quispe & Fiorella Torres & Melissa Zamudio & Ricardo Antiparra & L Mario Amzel & Robert H Gilman & , 2020. "Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-26, July.
  40. Loyer, Jean-Loup & Henriques, Elsa & Fontul, Mihail & Wiseall, Steve, 2016. "Comparison of Machine Learning methods applied to the estimation of manufacturing cost of jet engine components," International Journal of Production Economics, Elsevier, vol. 178(C), pages 109-119.
  41. Matheus Henrique Dal Molin Ribeiro & Stéfano Frizzo Stefenon & José Donizetti de Lima & Ademir Nied & Viviana Cocco Mariani & Leandro dos Santos Coelho, 2020. "Electricity Price Forecasting Based on Self-Adaptive Decomposition and Heterogeneous Ensemble Learning," Energies, MDPI, vol. 13(19), pages 1-22, October.
  42. Eslahi, Mohammadehsan & Mazza, Paolo, 2023. "Can weather variables and electricity demand predict carbon emissions allowances prices? Evidence from the first three phases of the EU ETS," Ecological Economics, Elsevier, vol. 214(C).
  43. Daoud, Adel & Kim, Rockli & Subramanian, S.V., 2019. "Predicting women's height from their socioeconomic status: A machine learning approach," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
  44. Vincenzo Cribari & Michael P. Strager & Aaron E. Maxwell & Charles Yuill, 2021. "Landscape Changes in the Southern Coalfields of West Virginia: Multi-Level Intensity Analysis and Surface Mining Transitions in the Headwaters of the Coal River from 1976 to 2016," Land, MDPI, vol. 10(7), pages 1-32, July.
  45. Christopher Kohl & Marlene Knigge & Galina Baader & Markus Böhm & Helmut Krcmar, 2018. "Anticipating acceptance of emerging technologies using twitter: the case of self-driving cars," Journal of Business Economics, Springer, vol. 88(5), pages 617-642, July.
  46. Verena Turco & Kira Pfleiderer & Jessica Hunger & Natalie K. Horvat & Kianush Karimian-Jazi & Katharina Schregel & Manuel Fischer & Gianluca Brugnara & Kristine Jähne & Volker Sturm & Yannik Streibel , 2023. "T cell-independent eradication of experimental glioma by intravenous TLR7/8-agonist-loaded nanoparticles," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
  47. Ribeiro, Matheus Henrique Dal Molin & da Silva, Ramon Gomes & Ribeiro, Gabriel Trierweiler & Mariani, Viviana Cocco & Coelho, Leandro dos Santos, 2023. "Cooperative ensemble learning model improves electric short-term load forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
  48. Razavi, Rouzbeh & Gharipour, Amin & Fleury, Martin & Akpan, Ikpe Justice, 2019. "A practical feature-engineering framework for electricity theft detection in smart grids," Applied Energy, Elsevier, vol. 238(C), pages 481-494.
  49. Fernando Delbianco & Fernando Tohmé, 2023. "Individualized Conformal," Working Papers 247, Red Nacional de Investigadores en Economía (RedNIE).
  50. Francesco Sartor & Jonathan P. Moore & Hans-Peter Kubis, 2021. "Plasma Interleukin-10 and Cholesterol Levels May Inform about Interdependences between Fitness and Fatness in Healthy Individuals," IJERPH, MDPI, vol. 18(4), pages 1-19, February.
  51. Gero Szepannek, 2022. "An Overview on the Landscape of R Packages for Open Source Scorecard Modelling," Risks, MDPI, vol. 10(3), pages 1-33, March.
  52. Maëva Labouyrie & Cristiano Ballabio & Ferran Romero & Panos Panagos & Arwyn Jones & Marc W. Schmid & Vladimir Mikryukov & Olesya Dulya & Leho Tedersoo & Mohammad Bahram & Emanuele Lugato & Marcel G. , 2023. "Patterns in soil microbial diversity across Europe," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
  53. Zander S. Venter & Adam Sadilek & Charlotte Stanton & David N. Barton & Kristin Aunan & Sourangsu Chowdhury & Aaron Schneider & Stefano Maria Iacus, 2021. "Mobility in Blue-Green Spaces Does Not Predict COVID-19 Transmission: A Global Analysis," IJERPH, MDPI, vol. 18(23), pages 1-12, November.
  54. Maria Victoria Bascon & Tomohiro Nakata & Satoshi Shibata & Itsuki Takata & Nanami Kobayashi & Yusuke Kato & Shun Inoue & Kazuyuki Doi & Jun Murase & Shunsaku Nishiuchi, 2022. "Estimating Yield-Related Traits Using UAV-Derived Multispectral Images to Improve Rice Grain Yield Prediction," Agriculture, MDPI, vol. 12(8), pages 1-28, August.
  55. Dario Krpan & Jonathan E. Booth & Andreea Damien, 2023. "The positive–negative–competence (PNC) model of psychological responses to representations of robots," Nature Human Behaviour, Nature, vol. 7(11), pages 1933-1954, November.
  56. Matthew N Ahmadi & Alok Chowdhury & Toby Pavey & Stewart G Trost, 2020. "Laboratory-based and free-living algorithms for energy expenditure estimation in preschool children: A free-living evaluation," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-14, May.
  57. María Bueno Álvez & Fredrik Edfors & Kalle Feilitzen & Martin Zwahlen & Adil Mardinoglu & Per-Henrik Edqvist & Tobias Sjöblom & Emma Lundin & Natallia Rameika & Gunilla Enblad & Henrik Lindman & Marti, 2023. "Next generation pan-cancer blood proteome profiling using proximity extension assay," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  58. Angham Daiyoub & Pere Gelabert & Sandra Saura-Mas & Cristina Vega-Garcia, 2023. "War and Deforestation: Using Remote Sensing and Machine Learning to Identify the War-Induced Deforestation in Syria 2010–2019," Land, MDPI, vol. 12(8), pages 1-18, July.
  59. Pauline Affeldt, 2019. "EU Merger Policy Predictability Using Random Forests," Discussion Papers of DIW Berlin 1800, DIW Berlin, German Institute for Economic Research.
  60. Yves Staudt & Joël Wagner, 2021. "Assessing the Performance of Random Forests for Modeling Claim Severity in Collision Car Insurance," Risks, MDPI, vol. 9(3), pages 1-28, March.
  61. Oluwaseyi Olalekan Arowosegbe & Martin Röösli & Nino Künzli & Apolline Saucy & Temitope Christina Adebayo-Ojo & Mohamed F. Jeebhay & Mohammed Aqiel Dalvie & Kees de Hoogh, 2021. "Comparing Methods to Impute Missing Daily Ground-Level PM 10 Concentrations between 2010–2017 in South Africa," IJERPH, MDPI, vol. 18(7), pages 1-13, March.
  62. Guopeng Jiang & Miles Grafton & Diane Pearson & Mike Bretherton & Allister Holmes, 2019. "Integration of Precision Farming Data and Spatial Statistical Modelling to Interpret Field-Scale Maize Productivity," Agriculture, MDPI, vol. 9(11), pages 1-22, November.
  63. Nyamekye, Clement & Kwofie, Samuel & Ghansah, Benjamin & Agyapong, Emmanuel & Boamah, Linda Appiah, 2020. "Assessing urban growth in Ghana using machine learning and intensity analysis: A case study of the New Juaben Municipality," Land Use Policy, Elsevier, vol. 99(C).
  64. G. Brooke Anderson & Keith W. Oleson & Bryan Jones & Roger D. Peng, 2018. "Classifying heatwaves: developing health-based models to predict high-mortality versus moderate United States heatwaves," Climatic Change, Springer, vol. 146(3), pages 439-453, February.
  65. Ramaharo, Franck Maminirina & RANDRIAMIFIDY, Michael Fitiavana, 2023. "Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms," AfricArxiv pfrhx, Center for Open Science.
  66. Yazan F. Roumani, 2023. "Sports analytics in the NFL: classifying the winner of the superbowl," Annals of Operations Research, Springer, vol. 325(1), pages 715-730, June.
  67. Van Belle, Jente & Guns, Tias & Verbeke, Wouter, 2021. "Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains," European Journal of Operational Research, Elsevier, vol. 288(2), pages 466-479.
  68. José R. Berrendero & Javier Cárcamo, 2019. "Linear components of quadratic classifiers," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(2), pages 347-377, June.
  69. Jorge Torres & María Muñoz & María Del Carmen Porcel & Sofía Contreras & Francisca Sonia Molina & Guillermo Rus & Olga Ocón-Hernández & Juan Melchor, 2022. "Preliminary Results on the Preinduction Cervix Status by Shear Wave Elastography," Mathematics, MDPI, vol. 10(17), pages 1-14, September.
  70. Sharan Srinivas, 2020. "A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers," IJERPH, MDPI, vol. 17(10), pages 1-15, May.
  71. Hory Chikez & Dirk Maier & Sigurdur Olafsson & Steve Sonka, 2023. "Identifying Critical Drivers of Mango, Tomato, and Maize Postharvest Losses (PHL) in Low-Income Countries and Predicting Their Impact," Agriculture, MDPI, vol. 13(10), pages 1-27, September.
  72. Yang, Yi & Li, Bingbing & Shi, Peijun & Li, Zhi, 2023. "Assessing spatiotemporally varied ecohydrological effects of apple orchards based on regional-scale estimation of tree distribution and ages," Agricultural Water Management, Elsevier, vol. 287(C).
  73. Alfaro, Esteban & Gamez, Matias & García, Noelia, 2013. "adabag: An R Package for Classification with Boosting and Bagging," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 54(i02).
  74. Feuerriegel, Stefan & Gordon, Julius, 2019. "News-based forecasts of macroeconomic indicators: A semantic path model for interpretable predictions," European Journal of Operational Research, Elsevier, vol. 272(1), pages 162-175.
  75. Kresova, Svetlana & Hess, Sebastian, 2021. "Determinants of Regional Raw Milk Prices in Russia," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317051, German Association of Agricultural Economists (GEWISOLA).
  76. Konstantinos Karyotis & Theodora Angelopoulou & Nikolaos Tziolas & Evgenia Palaiologou & Nikiforos Samarinas & George Zalidis, 2021. "Evaluation of a Micro-Electro Mechanical Systems Spectral Sensor for Soil Properties Estimation," Land, MDPI, vol. 10(1), pages 1-16, January.
  77. Edouard Ribes, 2022. "Using classification techniques to accelerate client discovery: a case study for wealth management services," Working Papers hal-03887759, HAL.
  78. Wen-Long Sun & Sha Hua & Xin-Yu Li & Liang Shen & Hao Wu & Hong-Fang Ji, 2023. "Microbially produced vitamin B12 contributes to the lipid-lowering effect of silymarin," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
  79. Yang Yue & Yingjie Jiang & Fan Zhou & Yuantao Jiang & Yiting Long & Kaiyu Wang, 2022. "Reward Uncertainty and Expected Value Enhance Generalization of Episodic Memory," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
  80. Zhonghyun Kim & Taeyong Shim & Seo Jin Ki & Dongil Seo & Kwang-Guk An & Jinho Jung, 2021. "Evaluation of Classification Algorithms to Predict Largemouth Bass ( Micropterus salmoides ) Occurrence," Sustainability, MDPI, vol. 13(17), pages 1-11, August.
  81. Zazueta, Jorge & Zazueta-Hernández, Jorge & Heredia, Andrea Chavez, 2023. "Support Vector Machines and Bankruptcy Prediction," SocArXiv 7z24k, Center for Open Science.
  82. Mario Aurelio Martínez-Jiménez & Jose Luis Ramirez-GarciaLuna & Eleazar Samuel Kolosovas-Machuca & Justin Drager & Francisco Javier González, 2018. "Development and validation of an algorithm to predict the treatment modality of burn wounds using thermographic scans: Prospective cohort study," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-16, November.
  83. Yrjö Lappalainen & Matti Lassila & Tanja Heikkilä & Jani Nieminen & Tapani Lehtilä, 2023. "Migrating 120,000 Legacy Publications from Several Systems into a Current Research Information System Using Advanced Data Wrangling Techniques," Publications, MDPI, vol. 11(4), pages 1-16, November.
  84. Denis S. Zavorotnyuk & Anatoly A. Sorokin & Stanislav I. Pekov & Denis S. Bormotov & Vasiliy A. Eliferov & Konstantin V. Bocharov & Eugene N. Nikolaev & Igor A. Popov, 2023. "Shapley Value as a Quality Control for Mass Spectra of Human Glioblastoma Tissues," Data, MDPI, vol. 8(1), pages 1-9, January.
  85. Alexander Wettstein & Gabriel Jenni & Ida Schneider & Fabienne Kühne & Martin grosse Holtforth & Roberto La Marca, 2023. "Predictors of Psychological Strain and Allostatic Load in Teachers: Examining the Long-Term Effects of Biopsychosocial Risk and Protective Factors Using a LASSO Regression Approach," IJERPH, MDPI, vol. 20(10), pages 1-20, May.
  86. Tang, Kayu & Parsons, David J. & Jude, Simon, 2019. "Comparison of automatic and guided learning for Bayesian networks to analyse pipe failures in the water distribution system," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 24-36.
  87. Michael J. Geuenich & Dae-won Gong & Kieran R. Campbell, 2024. "The impacts of active and self-supervised learning on efficient annotation of single-cell expression data," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  88. M. Ponziani & D. Ponziani & A. Giorgi & H. Stevenin & S. M. Ratto, 2023. "The use of machine learning techniques for a predictive model of debris flows triggered by short intense rainfall," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(1), pages 143-162, May.
  89. Andrée, Bo Pieter Johannes & Chamorro, Andres & Spencer, Phoebe & Koomen, Eric & Dogo, Harun, 2019. "Revisiting the relation between economic growth and the environment; a global assessment of deforestation, pollution and carbon emission," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
  90. Salamalikis, Vasileios & Tzoumanikas, Panayiotis & Argiriou, Athanassios A. & Kazantzidis, Andreas, 2022. "Site adaptation of global horizontal irradiance from the Copernicus Atmospheric Monitoring Service for radiation using supervised machine learning techniques," Renewable Energy, Elsevier, vol. 195(C), pages 92-106.
  91. Dobbs, Cynnamon & Eleuterio, Ana Alice & Vásquez, Alexis & Cifuentes-Ibarra, Mauricio & da Silva, Demóstenes & Devisscher, Tahia & Baptista, Mariana Dias & Hernández-Moreno, Ángela & Meléndez-Ackerman, 2023. "Are we promoting green cities in Latin America and the Caribbean? Exploring the patterns and drivers of change for urban vegetation," Land Use Policy, Elsevier, vol. 134(C).
  92. Siddharth Sethi & David Zhang & Sebastian Guelfi & Zhongbo Chen & Sonia Garcia-Ruiz & Emmanuel O. Olagbaju & Mina Ryten & Harpreet Saini & Juan A. Botia, 2022. "Leveraging omic features with F3UTER enables identification of unannotated 3’UTRs for synaptic genes," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
  93. Takuji Matsumoto & Yuji Yamada, 2021. "Comprehensive and Comparative Analysis of GAM-Based PV Power Forecasting Models Using Multidimensional Tensor Product Splines against Machine Learning Techniques," Energies, MDPI, vol. 14(21), pages 1-22, November.
  94. Ramalingam Kumaraperumal & Sellaperumal Pazhanivelan & Vellingiri Geethalakshmi & Moorthi Nivas Raj & Dhanaraju Muthumanickam & Ragunath Kaliaperumal & Vishnu Shankar & Athira Manikandan Nair & Manoj , 2022. "Comparison of Machine Learning-Based Prediction of Qualitative and Quantitative Digital Soil-Mapping Approaches for Eastern Districts of Tamil Nadu, India," Land, MDPI, vol. 11(12), pages 1-26, December.
  95. Svetlana Kresova & Sebastian Hess, 2022. "Identifying the Determinants of Regional Raw Milk Prices in Russia Using Machine Learning," Agriculture, MDPI, vol. 12(7), pages 1-18, July.
  96. Paola Perchinunno & Massimo Bilancia & Domenico Vitale, 2021. "A Statistical Analysis of Factors Affecting Higher Education Dropouts," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 341-362, August.
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